Evidence From The Housing Market in New York City
Old Dominion University
via The Wall Street Journal
Stop & Frisk by Day in New York City
Crime Reports by Day in New York City
Tita, Petras, and Greenbaum (2006); Ihlanfeldt and Mayock (2010); Linden and Rockoff (2008); Pope (2008); Caudill, Affuso, and Yang (2015); Kim and Lee (2018)
Does the way we are policed effect housing prices?
MacDonald, Fagan, and Geller (2016)
In January 2003, the NYPD deployed roughly two-thirds of its police academy graduates—about 1,500 new police officers—to Impact Zones.
Police Commanders nominated crime “hot spots” within their precincts
Every 6 months, these zones would be re-evaluated and adjusted.
I want to know how property prices changes after Stop & Frisk was ruled unconstitutional.
Idea 1: Calculate Average Prices Before & After
This won’t work because there might be price dynamics going on in NYC that occur at the same time as the Floyd case. How can I be sure I am not capturing those effects?
I want to know how property prices changes after Stop & Frisk was ruled unconstitutional.
Idea 1: Calculate Average Prices Before & After
This won’t work because there might be price dynamics going on in NYC that occur at the same time as the Floyd case. How can I be sure I am not capturing those effects?
Idea 2: Calculate Difference in Prices between Treatment and Control
This won’t work because there might be pre-existing differences between treatment and control. How can I be sure I am not capturing those effects?
I want to know how property prices changes after Stop & Frisk was ruled unconstitutional.
Idea 1: Calculate Average Prices Before & After
This won’t work because there might be price dynamics going on in NYC that occur at the same time as the Floyd case. How can I be sure I am not capturing those effects?
Idea 2: Calculate Difference in Prices between Treatment and Control
This won’t work because there might be pre-existing differences between treatment and control. How can I be sure I am not capturing those effects?
Idea 3: Combine Ideas 1 and 2
Calculate difference (before and after) for both treatment and control. Whatever happened in the control should have also happened in the treatment. Subtracting the change in the control from the change in the treatment will isolate the treatment effect.
I want to know how property prices changes after Stop & Frisk was ruled unconstitutional.
Idea 1: Calculate Average Prices Before & After
This won’t work because there might be price dynamics going on in NYC that occur at the same time as the Floyd case. How can I be sure I am not capturing those effects?
Idea 2: Calculate Difference in Prices between Treatment and Control
This won’t work because there might be pre-existing differences between treatment and control. How can I be sure I am not capturing those effects?
Idea 3: Combine Ideas 1 and 2
Calculate difference (before and after) for both treatment and control. Whatever happened in the control should have also happened in the treatment. Subtracting the change in the control from the change in the treatment will isolate the treatment effect. This is called difference-in-differences.
\[\begin{align}P_{int} &= X_{int}\beta + \delta_1 \text{Floyd}_{t} + \delta_2 \text{Impact}_{i} \\ &+ \delta_3 (\text{Floyd}_{t} \times \text{Impact}_{i}) + \epsilon_{int}\end{align}\]
\(\delta_3\) is the “treatment effect”: how much more did properties prices change in Impact Zones, relative to nearby properties, when Stop & Frisk was ruled unconstitutional.
If property prices for both areas changed in similar ways, \(\delta_3 \approx 0\).
Time Series of Sale Price
\[\begin{align}P_{int} & = X_{int}\beta + \delta_1 \text{Floyd}_{t} + \delta_2 \text{Impact}_{i} \\ & + \delta_3 (\text{Floyd}_{t}\times \text{Impact}_{i}) + \lambda_1 \text{NonWhite}_{it} \\ & + \lambda_2 (\text{Impact}_{i}\times \text{NonWhite}_{it}) + \lambda_3 (\text{Floyd}_{t}\times \text{NonWhite}_{it}) \\ & + \lambda_4 (\text{Floyd}_{t}\times \text{Impact}_{i}\times \text{NonWhite}_{it}) + \epsilon_{int}\end{align}\]
\[\begin{align} P_{int} &= X_{int}\beta + \delta_1 \text{Floyd}_{t} + \delta_2 \text{Impact}_{i} \\ & + \delta_3 (\text{Floyd}_{t} \times \text{Impact}_{i}) + \gamma_1 (\text{Impact}_{i} \times \text{Exposure}_{it}) \\ & + \gamma_2 (\text{Floyd}_{t} \times \text{Impact}_{i} \times \text{Exposure}_{it}) + \epsilon_{int}\end{align}\]
University of Louisiana at Lafayette